For fixed source problems, it is known that the analog Monte Carlo simulation method can show low efficiencies. To increase the calculation efficiency, variance reduction techniques (VRT) have been introduced and utilized. To apply these techniques, parameters to control particle transport behaviors should be properly determined. The hybrid Monte Carlo methods were developed to automatically determine the VRT parameters using information estimated from a deterministic simulation. In the case of a single response, the Consistent Adjoint Driven Importance Sampling (CADIS) method is well derived to decide VRT parameters. Recently, for plural response problems, a variety of methods have been proposed. It is noted that Forward-Weighted CADIS (FW...
The complexity of integrands in modern scientific, industrial and financial problems increases rapid...
Graduation date: 2011Adjoint-derived weight windowing is a hybrid deterministic/Monte Carlo method t...
[[abstract]]A computer algorithm which combines several variance reduction techniques to enhance the...
Monte Carlo methods are used to compute fluxes or dose rates over large areas using mesh tallies. Fo...
Neutral particle radiation transport simulations are critical for radiation shielding and deep penet...
For challenging radiation transport problems, hybrid methods combine the accuracy of Monte Carlo met...
The application of Monte Carlo (MC) to large-scale fixed-source problems has recently become possibl...
In radiation protection studies, the goal is to estimate the response of a detector exposed to a str...
Methods for deep-penetration radiation transport remain important for radiation shielding, nonprolif...
International audienceVariance reduction is a key ingredient for solving radiation-protection proble...
International audienceVariance reduction is a key ingredient for solving radiation-protection proble...
This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods a...
The development of methods for deep-penetration radiation transport is of continued importance for r...
Graduation date: 2016The implementation of advanced hybrid (Monte Carlo/Deterministic) transport met...
The author derives a transformed transport problem that can be solved theoretically by analog Monte ...
The complexity of integrands in modern scientific, industrial and financial problems increases rapid...
Graduation date: 2011Adjoint-derived weight windowing is a hybrid deterministic/Monte Carlo method t...
[[abstract]]A computer algorithm which combines several variance reduction techniques to enhance the...
Monte Carlo methods are used to compute fluxes or dose rates over large areas using mesh tallies. Fo...
Neutral particle radiation transport simulations are critical for radiation shielding and deep penet...
For challenging radiation transport problems, hybrid methods combine the accuracy of Monte Carlo met...
The application of Monte Carlo (MC) to large-scale fixed-source problems has recently become possibl...
In radiation protection studies, the goal is to estimate the response of a detector exposed to a str...
Methods for deep-penetration radiation transport remain important for radiation shielding, nonprolif...
International audienceVariance reduction is a key ingredient for solving radiation-protection proble...
International audienceVariance reduction is a key ingredient for solving radiation-protection proble...
This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods a...
The development of methods for deep-penetration radiation transport is of continued importance for r...
Graduation date: 2016The implementation of advanced hybrid (Monte Carlo/Deterministic) transport met...
The author derives a transformed transport problem that can be solved theoretically by analog Monte ...
The complexity of integrands in modern scientific, industrial and financial problems increases rapid...
Graduation date: 2011Adjoint-derived weight windowing is a hybrid deterministic/Monte Carlo method t...
[[abstract]]A computer algorithm which combines several variance reduction techniques to enhance the...